Abstract
BACKGROUND: Carbapenem-resistant Acinetobacter baumannii (CRAB) remains a major challenge in intensive care units (ICUs), posing substantial risks for colonization, infection, and transmission. Timely identification of patients at risk for hospital-acquired CRAB is essential to guide infection prevention and control efforts. This study aimed to develop and internally validate a nomogram for individualized risk prediction of hospital-acquired CRAB colonization or infection among critically ill patients. METHODS: A retrospective multicenter cohort study was performed including 7,060 ICU patients admitted to two tertiary hospitals in China between January 1, 2019 and December 31, 2024. Candidate predictors were identified through univariate logistic regression and further refined using multivariate logistic regression with backward stepwise selection. A nomogram was subsequently constructed based on the final regression model to predict individualized risk of hospital-acquired CRAB. Model performance was evaluated in separate training and validation cohorts using area under the receiver operating characteristic curve (AUC), calibration plots, and decision curve analysis (DCA). RESULTS: Hospital-acquired CRAB colonization or infection was observed in 224 patients (3.17%). Six independent risk factors were retained in the final model: carbapenem exposure, presence of other multidrug-resistant organisms (MDROs), mechanical ventilation, number of ICU admissions, ICU length of stay, and hospital length of stay. The nomogram exhibited strong discriminative capacity (AUC = 0.824 in the training cohort; 0.789 in the validation cohort) and demonstrated good calibration across both cohorts. DCA indicated a consistent net clinical benefit across a wide range of threshold probabilities. A risk cutoff of 0.022 (derived from the Youden index) was selected to prioritize sensitivity for infection prevention in this low-incidence setting. CONCLUSION: This internally validated nomogram provides an accessible tool for early identification of ICU patients at elevated risk of hospital-acquired CRAB colonization or infection. Its integration into clinical practice may facilitate risk-based prevention strategies. Future research should focus on prospective external validation and integration of environmental surveillance and microbiological genomic data to enhance the model's predictive accuracy and generalizability.